Jason Hiltz-laforge
Director - Production Engineering at Shopify
Ottawa, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolJason Hiltz-laforge is a seasoned production engineering leader with 12+ years driving the scalability, performance, and reliability of large-scale infrastructure at Shopify. As Director of Production Engineering he leads teams responsible for operational data stores, caching, streaming, search and job processing, blending hands-on performance engineering with strategic org leadership. His background spans systems and SRE roles at Shopify and IBM, where he delivered measurable improvements in database, search and streaming platforms using technologies like MySQL, Redis, Elasticsearch, Kafka and Kubernetes. Jason is also an effective performance-focused back-end engineer—his open-source contributions to Shopify’s widely used Liquid template engine emphasize profiling, refactors to cut allocations, and caching to accelerate rendering. Known for moving from deep technical work into leadership without losing sight of low-level optimizations, he combines operational rigor with a track record of mentoring teams to run resilient, high-throughput services. Based in Ottawa, he brings practical systems insight rooted in decades of performance and scalability problem-solving.
12 years of coding experience
20 years of employment as a software developer
Algonquin CollegeUniversity of Ottawa
French, English
Github Skills (5)
testing10
ruby10
performance-optimization10
profiling10
caching9
Programming languages (4)
Github contributions (5)
Shopify/liquid
Jul 2014 - Sep 2014
Liquid markup language. Safe, customer facing template language for flexible web apps.
Role in this project:
Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:20 commits, 3 comments in 1 month
Contributions summary:Jason primarily focused on optimizing the performance of the Liquid markup language. Their contributions involved refactoring code to reduce object allocation, caching parsed markup for efficiency, and replacing inefficient methods with more performant alternatives. They also implemented object and CPU profiling to identify bottlenecks within the system, improving overall rendering speed. Furthermore, the user added tests and dependencies related to testing the optimized and refactored code.
markup-language
jasonhl/rails
Apr 2020 - Sep 2020
Ruby on Rails
Contributions:15 pushes, 3 branches in 4 months
ruby-on-railshamlrailsrubyruby-on
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